80% Faster Bank Reconciliation Through RPA-Driven Automation
The project was designed to automate the complete bank reconciliation process by eliminating the manual effort involved in matching bank transactions with Oracle ERP financial records. Using RPA and rule-based automation, MT940 bank statements are automatically read, transaction types are identified and classified, and bank entries are matched with corresponding ERP records. Reconciled entries are then automatically created in Oracle ERP, resulting in significantly faster reconciliation cycles, improved data accuracy, and more timely and reliable financial reporting.
Client Overview
The client is a leading enterprise operating across multiple business segments with high volumes of bank transactions. The finance team performs daily and monthly bank reconciliations for multiple bank accounts. It requires an automated solution to reduce processing time, minimize errors, and ensure accurate and timely financial data.
Technical Stack
Industry
Investment Management
Region
UAE (Sultanate-wide implementation)
Project-size
Non-Disclosable
Company size
Large Scale Authority (National Government Body)
Implementation Highlights
Automated MT940 statement processing: Enabled automated ingestion and reading of MT940 bank statements from multiple banks, ensuring consistent interpretation and accurate extraction of transaction data.
Rule-based transaction categorisation: Implemented a business-rules engine to intelligently classify transactions such as payments, receipts, cheques, SWIFT transfers, POS settlements, and bank charges.
ERP-driven transaction matching: Matched bank transactions with Oracle ERP records using reference numbers, amount matching, pattern recognition, and date tolerance to maximise auto-match accuracy.
Automated ERP reconciliation posting:
Automatically generated reconciled journal entries in Oracle ERP, eliminating manual posting effort and ensuring timely and accurate financial reporting.
Challenges & Solutions
Handling Complex and Inconsistent MT940 File Structures Across Multiple Banks
Solution: A robust MT940 parser was developed to recognise all MT940 tag types and variations. Fallback logic and rule-based identification were built in to handle exceptions and incomplete data, ensuring every file could be interpreted accurately regardless of the originating bank.
Managing Multiple Transaction Categories and Business Exceptions During Reconciliation
Solution: A configurable rules engine was built within the RPA platform to classify transactions based on business logic intelligently. This allowed the bot to automatically identify and categorise each transaction type, manage exceptions, and ensure consistent handling across all bank accounts.
Achieving Accurate Matching with Oracle ERP Despite Limited and Inconsistent Reference Data
Solution: Advanced SQL-based pattern search logic was implemented to compare multiple matching parameters, including amount, reference fields, vendor names, cheque numbers, and date tolerances. This significantly increased auto-match rates, even when complete references were not available.
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Results & Impact
- Achieved up to 80% faster bank reconciliation cycles — reducing processing time from hours to just minutes per day.
- Significantly reduced month-end closing time by automating high-volume reconciliation activities across multiple bank accounts.
- Delivered 100% accuracy for all rule-based transaction categorisation, eliminating errors caused by manual interpretation.
- Improved financial reporting reliability through consistent, audit-ready reconciliation records with full exception visibility.
Key Learnings & Achievement
- Developed a reusable, scalable, and audit-ready bank reconciliation automation framework that standardizes reconciliation processes and can be directly leveraged for future projects across banks and entities.
- Effective handling of multi-bank MT940 files requires strong parsing, accurate reference extraction, and a hybrid RPA + SQL + ERP approach, along with structured exception reporting to ensure accuracy, transparency, and audit readiness.
